Objective To explore the risks and causes of terminal displacement control after emergency stop of medical surgical robots, design test methods, conduct actual tests, analyze the influencing factors of terminal displacement after emergency stop based on the results, and clarify the measurement conditions of this index.Methods The emergency stop signal of the robotic arm was elicited, and the spatial coordinates of the reference point at the end of the robotic arm were collected continuously and quickly by the non-contact space measurement device when the emergency stop was pressed. The influence of static or moving along different vector directions at different speeds on the end displacement after emergency stop was analyzed under different emergency stop control modes, and the influence of these parameters on the test results was compared and analyzed by one-way ANOVA.Results Through the experiments designed in this paper, it was found that the initial and final displacement of the emergency stop and the maximum displacement of the emergency stop of the robotic arm were significantly different, and the difference could be 0.49-1.61 mm in different vector directions and 0.18-0.57 mm at different speeds. For some models of robotic arms, the difference in emergency stop control modes could cause a displacement difference of more than 10 mm. At the same time, the posture during emergency stop also had a certain degree of influence on the displacement at the end of the robotic arm after emergency stop.Conclusion This paper designs a scientific and effective testing method, which can test the maximum displacement at the end and the initial and final displacement of medical surgical robots after emergency stop. When conducting tests, the influence of running speed, emergency stop control methods and the posture during emergency stops on the results should be fully considered.

Objective To discuss the influence of linear and parabolic air resistance on the capacity control of ventilator according to the new requirements of GB 9706.212-2020 standard for control accuracy, and provide guidance for optimizing the control algorithm and detection specification of ventilator.Methods In this paper, the hydrodynamic characteristics of linear and parabolic impediments and their effects on the control accuracy of tidal volume were compared by ventilator ventilation experiment.Results The experimental results showed that the control error of a ventilator was 9.6% when using parabolic resistance under R5 conditions. When linear resistance was used, the control error increased to -39.0%, and the flow value in the airway decreased significantly. Tidal volume control behaves differently with different resistance settings, especially at low resistance settings where linear resistance resistance may lead to large tidal volume errors.Conclusion Simulated pulmonary resistance can affect the accuracy of tidal volume output of ventilators. Manufacturers need to optimize the control algorithm according to the new standard to ensure that the equipment meets the requirements.

Objective To analyze the numerous challenges encountered in the classification of P300 visual evoked potential signals and to investigate novel prospective solutions.Methods This study introduced a novel KAN neural network model, augmented with a convolutional self-attention mechanism. This innovative approach proficiently captured the global feature information of P300 signals. Furthermore, the incorporation of the KAN layer enhanced its capability to manage nonlinear data effectively. To validate the efficacy of this model, experiments were executed utilizing the widely recognized brain computer interface Competition Ⅲ Challenge 2004 dataset. The performance of our proposed model was subsequently juxtaposed with modern P300 VEP classification techniques.Results The proposed model exhibited superior classification accuracy on the validation set, achieving an impressive 100.0% accuracy in P300 signal classification. This performance surpassed that of VGG-16, which achieved 98.9%, and ResNet-18, which achieved 99.0%. Furthermore, in experiments involving fast gradient sign methed attacks, the model maintained an accuracy of 82%.Conclusion This study presents a novel methodology for the classification of P300 VEP signals, which can also be applied to similar tasks in brain signal processing. This offers fresh research perspectives and contributes to the progression of brain signal research.

Objective To propose a multimodal magnetic resonance imaging (MRI) image fusion and segmentation method, and combine different sequence images under MRI to improve the segmentation accuracy of organs in the spinal region.Methods A dual-branch fusion segmentation network was designed for T1 and T2 modal images under MRI. Firstly, the features in a single modality were extracted by using a hybrid encoder. Then, the cross-modal features were extracted through the Transformer structure. Finally, in the upsampling stage, the multi-modal information was fused based on the spatial attention mechanism to complete the segmentation. Furthermore, a deep supervision mechanism was adopted to improve the efficiency of network training. Experiments were conducted on the lumbar spine MRI dataset SPIDER. The method proposed in this paper was compared with the traditional single-modal segmentation method and other fusion segmentation methods to verify the effectiveness of feature fusion of the method proposed in this paper.Results The Dice coefficients of the proposed method in this paper for segmentation on vertebrae, intervertebral discs and spinal canals were 93.20%, 86.90% and 94.80% respectively, which were superior to the traditional single-modal image segmentation methods. Moreover, the proposed method in this paper was more robust in the case of modal absence.Conclusion The multimodal MRI image fusion and segmentation method proposed in this paper can effectively combine the respective imaging advantages of the T1 and T2 modalities, improve the segmentation accuracy of organs in the spinal region, assist doctors in diagnosis in clinical applications, and improve the efficiency of diagnosis and treatment.

Objective To explore the risk factors affecting the stability of gold fiducial markers (GFM) after implantation in prostate cancer (PCa) image guided radiotherapy (IGRT) and construct a Nomogram prediction model.Methods A total of 500 patients who underwent PCa IGRT and had GFM implanted in the First Affiliated Hospital of Hebei North University from January 2016 to June 2024 were selected as the research subjects and divided into the modeling group (n=300) and the validation group (n=200).The stability of GFM after implantation was evaluated by the markers spacing. According to the evaluation results, the patients in the modeling group were divided into the GFM stable group (n=200) and the unstable group (n=100). The Logistic regression program was compiled using the R language 4.0 “rms” software package to analyze the independent risk factors affecting stability. Substitute the factorized independent risk factors into the Nomogram prediction model construction program and draw the Nomogram graph; The internal verification of the model was accomplished by using the concordance index (C-index), calibration curve and decision curve. The area under the receiver operating characteristic curve (AUC) was used to evaluate and compare the efficacy of the model in predicting the stability of the modeling group and the validation group, and the external validation of the model was completed.Results There was no statistically significant difference in the baseline data between the modeling group and the validation group (P>0.05).There were statistically significant differences in baseline data such as prostate specific antigen, gleason score, prostate volume (PV), the number of GFM implants, implantation sites, and the ratio of surface distance along the central axis between the stable group and the unstable group (P<0.1). PV<25 mL, the number of GFM implants (4 markers), the implantation site of GFM (bottom), and the ratio of the surface distance of the central axis of GFM (3∶1) were independent risk factors affecting the stability after GFM implantation. Internal verification: the C-index of the Nomogram model for predicting stability was 0.846 (95%CI: 0.692-0.931),with a threshold >0.25. The calibration curve showed good consistency between the observed values and the predicted values, and the decision curve indicated that the model could provide clinical net benefits and was higher than each independent predictor. External verification: the AUC values of the Nomogram model for predicting the stability of the modeling group and the verification group were both higher than those of each independent predictor. There was no statistically significant difference in the AUC between the two groups (P=0.446>0.05), and the curve fitting was relatively ideal (P=0.257>0.05).Conclusion The Nomogram model has an ideal predictive effect on the stability after GFM implantation in PCa IGRT, which can provide certain references for improving the safety of GFM application.

Objective To observe the efficacy and safety of sterile cold spray in alleviating the pain of venipesis and the resulting anxiety and fear in first-time blood donors and plasma donors, in order to determine the safety and efficacy of sterile cold spray in reducing the pain related to venipesis in donors.Methods An open label, randomized controlled, and multicenter approach was adopted. Experiments on relieving pain with sterile cold spray and reducing the tension and fear of donors were conducted respectively in blood stations and plasma stations for 480 first-time voluntary blood donors and 2296 plasma donors. Blood donors were randomly divided into the observation group (n=240) and the control group (n=240)), and plasma donors were randomly divided into the observation group (n=1146) and the control group (n=1150). Before venous puncture, the observation group was given sterile cold spray for pain intervention, and the sterile cold spray was sprayed at the puncture site for 4 to 10 seconds. The control group was operated as usual, and visual analogue scale and behavioral discipline assessment scale questionnaires were conducted for each group. Telephone follow-up survey was conducted on the willingness to donate blood for first-time blood donors; Telephone follow-up survey was conducted on the satisfaction of first-time plasma donors.Results There were no statistically significant differences among each group in terms of gender, educational background, age, height, weight and BMI (P>0.05). The pain score of the blood donor observation group was (2.75±1.85) points, and the anxiety score was (14.97±2.39) points. The pain score of the control group was (3.85±1.72) points, and the anxiety score was (16.76±2.62) points. The pain score of the plasma donor observation group was (2.67±1.87) points, and the anxiety score was (15.13±2.20) points. The pain score of the control group was (4.02±1.88) points and the anxiety score was (16.90±2.67) points. The differences between the two groups were statistically significant (P<0.001). In terms of the telephone follow-up on the willingness to donate blood, the proportion of the observation group willing to donate blood again was 72.1%, which was higher than 48.0% in the control group (P<0.001). For the telephone follow-up on the pain management satisfaction of plasma donors, the satisfaction rate of the observation group was 86.31%, which was higher than that of the control group (61.05%) (P<0.001).Conclusion The intervention of using sterile cold spray during venipesis for first-time blood donors or plasma donors can reduce their pain, relieve their anxiety, and is conducive to improving the willingness of donors to donate again.

Objective To explore the effect of dose escalation of Cyberknife radiotherapy (referred to as “radiotherapy”) on the therapeutic effect of locally advanced pancreatic cancer.Methods A total of 110 patients with locally advanced pancreatic cancer treated with Cyberknife at the Department of Radiotherapy of the 940th Hospital of Joint Logistic Support Force of PLA from January 2013 to June 2023 were selected as the research subjects and divided into 3 groups according to the radiotherapy dose: 35, 40, and 45 Gy. The median survival period and survival rate of the three groups were mainly observed. The local control rate and distant survival rate of the three groups were secondiously observed. The differences among the three groups were analyzed to see if they were statistically significant.Results The median survival time of 110 patients with locally advanced pancreatic cancer was 15 months. The 1-year survival rate was 65.2% (95%CI: 55.9%-76.2%), and the 2-year survival rate was 36.4% (95%CI: 26.4%-50.4%). The median survival periods of the 35, 40, and 45 Gy groups were 11, 20, and 25 months respectively, and the difference was statistically significant (χ²=12.789, P=0.002<0.05). Compared with the 35 Gy group, the median survival time of the 40 Gy group was significantly prolonged, and the difference was statistically significant (20 months vs. 11 months, χ²=7.070, P=0.008<0.05),while there was no statistically significant difference between the 40 Gy group and the 45 Gy group (χ²=0.744, P=0.388>0.05).The 1-year survival rates of the 35, 40, and 45 Gy groups were 46.0%, 64.9%, and 85.3% respectively; the 1-year local control rates were 48.4%, 55.4%, and 67.6% respectively; and the 1-year distant transfer-free survival rates were 57.4%, 74.5%, and 52.3% respectively. The differences in the maximum cross-sectional area and the tumor marker carbohydrate antigen 199 before and after treatment in 110 patients were statistically significant (P<0.05). The gastrointestinal toxic reactions and bone marrow toxic reactions of 110 patients were mainly grade 1 to 2.Conclusion With the increase of radiotherapy dose, the median survival time of patients with locally advanced pancreatic cancer treated with Cyberknife will gradually increase and will no longer increase after reaching a certain dose. With the increase of the total radiotherapy dose for patients with locally advanced pancreatic cancer, the local control rate will also increase, but the difference is not statistically significant.

Objective To verify the accuracy of dose calculation of the beam model established by the domestic TAICHI equipment in the RayStation treatment planning system, so that the equipment can better serve the treatment of clinical patients.Methods Based on the reports of MPPG 5.a and TG119 released by the American Association of Medical Physics, the model dose calculation model of the TAICHI equipment was verified, including PDD curves, Profile curves, TG119, and clinical case verification, etc.Results The gamma pass rates of 2 mm/2% from the basal field of different source skins at shallow depths (0-20 cm) were basically close to 100%. The results at deep depths (25 cm underwater) were worse than those at shallow depths, but the mean value was still above 93%. The dose deviation results at all points were less than 2% (after small field correction). Therefore, the beam current in the model was basically consistent with the actual output of the equipment. The results of gamma pass rates at both point doses and area doses of intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) for TG119 test cases were much better than the standards required by the TG119 report. The average deviation results of planned point dose verification for clinical patients in IMRT and VMAT were 0.48% and 0.47% respectively, and the gamma pass rates of 2 mm/2% and 3 mm/3% in surface dose tests were 95.58%, 99.46% and 96.75%, 99.30% respectively. All the results met the clinical needs. The end-to-end lung tests of IMRT and VMAT passed, and the point dose deviations were -0.495% and -2.602% respectively.Conclusion After being verified by the MPPG 5.a and TG119 systems, the results of domestic TAICHI meet and far exceed the reporting requirements and standards, conform to clinical requirements, and can be used to optimize the treatment plans of clinical patients. For cases with poor deep fitting, more attention is needed in the subsequent modeling process.

Objective To investigate the triggering factors of retrogressive dose iteration and the feasibility of the high-dose iteration position truncation calculation scheme of the Monaco treatment planning system (TPS) in radiotherapy for cervical cancer (referred to as “radiotherapy”).Methods Thirty patients who underwent volumetric modulated arctherapy (VMAT) for cervical cancer from June 1, 2023 to April 1, 2024 were selected as the research subjects. The prescribed dose was 45 Gy/25 F, and two full-arc VMAT plans were designed for each patient. After the flux optimization was completed, the modulation degree (MD) was statistically analyzed through the Progress Meter, and the experimental cases were divided into the High MD group and the Low MD group based on the difference rate. The difference rate between the results of flux optimization and dose optimization of planning target volume (PTV) V₄₅ (the percentage of organs receiving at least 45 Gy dose, and other similar) in the two groups was analyzed; The patients in the High MD group (Plan HLC) were further studied to analyze the differences in the V₄₅ of PTV and the dosimetry of major organs at risk (OARS), plan characteristic parameters, plan dose distribution and plan verification results between the high MD plan group and the conventional automatic completion plan group.Results The MD values of the 30 enrolled cases were statistically analyzed. There were 19 cases in the High MD group (MD>3), accounting for 63.3%, and 11 cases in the Low MD group (MD<3), accounting for 37.7%. The difference rate between the V₄₅ flux optimization result and the dose optimization result of PTV in the High MD group was significantly higher than that in the Low MD group. During the entire dose iteration process of the High MD group, a significant drop was observed after the V₄₅ of PTV reached its peak. In the further analysis of the experimental cases of Plan A and Plan HLC, the dose differences in the target area and the main OARs were statistically significant [V45 of PTV: t=3.116, P=0.013: Small intestine 0.03g (the maximum dose value of 0.03 cm³ by volume): t=1.241, P=0.022; Rectal: t=6.183, P=0.02; Bladder V₄₀: t=3.174, P=0.032]. The analysis of the dose cloud graph and the dose-volume histogram showed that the difference trends of the two groups were similar. The statistical results of the characteristic parameters of dose optimization indicated that the differences in each result between the two groups were statistically significant (dose optimization time of X-ray Monte Carlo algorithm: t=1.607, P=0.001; Planned photon utilization rate: t=4.962, P=0.023; Number of subfields: t=2.512, P=0.022; Machine hop count: t=8.201, P=0.001). The verification results of both groups of plans met the clinical requirements, but the Plan A group was slightly higher than the Plan HLC group.Conclusion When using Monaco5.11 TPS to optimize the radiotherapy plan for cervical cancer, the MD value is the main factor triggering retrogressive iterations. The high-dose iterative position cut-off Plan when degenerative iterations occur meets the clinical implementation conditions, and the obtained Plan HLC plan can be used for radiotherapy.

Objective To construct a prediction model for the setup error distribution of patients undergoing stereotactic body radiation therapy (SBRT).Methods The setup error data of 45 patients with SBRT who were treated with the Varian Vital Beam (SN3546) medical linear accelerator in the Department of Oncology Radiology of the Affiliated Hospital of Xuzhou Medical University from January 2019 to December 2022 were selected as the research objects. The error distribution prediction model was constructed by using the variational inference Bayesian Gaussian mixture model to solve the model parameters.Results The setup errors in the translation direction mainly concentrated in the three centers (μ1 to μ3) directions. The average offsets were relatively large in the front-back (-3.45 to 4.84 mm) and head-foot directions (0.22 to 5.67 mm), while the average offsets were relatively small in the left-right direction (0.14 to 0.79 mm). The possibility of offset of the setup error towards the center point of μ3 was the greatest, and the probability of the error center was 0.54. The possibility of offset towards μ1 was the smallest, and the probability of the error center was 0.20. The maximum variance in the translation direction was 1.72 mm. The setup errors in the rotation direction mainly concentrated in the directions of the four center points (μ1 to μ4). The average offsets in the tilt direction (-0.50° to 0.15°) and the rotation direction (-0.52° to -0.10°) were relatively larger than those in the rotation direction (0.03° to 0.25°). The possibility of the setup error offsetting towards the μ3 center point was the greatest, and the probability of the error center was 0.69. The offset possibilities of the remaining three center points were not much different. Compared with the translation direction, the variance values of each center in the rotation direction were larger except for the data of the μ2 center point (-0.52°), indicating that the data in the translation direction was more concentrated.Conclusion The variational inference Bayesian Gaussian mixture model can quantitatively describe and predict the setup error data, providing a reference for exploring the distribution regularity of SBRT setup errors.

Objective To solve the problems existing in clinical practical training within traditional Chinese medicine education and teaching such as low learning interest, relatively fragmented time, and rather monotonous learning and memorization methods, construct a traditional Chinese medicine clinical classic training platform based on the integration of information technology.Methods The SpringBoot development framework was utilized as the business processing technology, the visualization was achieved by WeChat mini-program, the MySQL+Redis was adopted for data storage. Meanwhile, the requirements of the traditional Chinese medicine clinical classic training platform were analyzed, and a message synchronization and algorithm matching scheme combining WebSocket technology and Redis storage framework was proposed to realize the core business functions of the platform.Results The test data of the chapter after the application of the platform showed that the time of using the platform for learning was (4.36±0.42) min, which was less than that of the platform not used (5.15±0.52) min, and the difference was statistically significant (t=2.368, P=0.012). The depth and breadth of users’ mastery of clinical knowledge of traditional Chinese medicine were significantly improved. Quantitative research on the impact of platform learning mode showed that the platform had achieved 4.95 points of promotion and application satisfaction, indicating that the platform played a positive role in the improvement of learning.Conclusion The traditional Chinese medicine clinical classic training platform improves the participation of clinical training, strengthens the mastery of clinical knowledge, integrates the time of students, effectively reduces the cost of learning and economy, which can promote the efficient development of classical training of traditional Chinese medicine.

Objective To solve the problems of low maintenance quality and efficiency under the traditional mode, to establish an information platform for operation training and fault maintenance of various medical equipment to provide standardized professional guidance, so as to improve the quality and efficiency of medical equipment maintenance.Methods Based on Python-Django framework and Vue framework, a technical support auxiliary system for medical equipment training, fault handling and quality control was built by using front-end and back-end separation technology. The use of mobile phone terminals was supported by the system, which could be used as a medical equipment teaching system, and had evaluation feedback function.Results After the operation of the system, the average daily number of equipment maintenance increased from 7.53±4.92 to 9.43±4.89, and the average daily failure repair rate increased from 78%±22% to 86%±14%, with statistical significance (P<0.05).Conclusion The medical equipment technical support auxiliary system digitizes the technical support data and provides professional guidance with a digital platform, which helps to improve the level of maintenance management. It is an iteratively updated maintenance knowledge base.

Objective To design a set of efficient and easy-to-use server ledger management system to cope with the problem of hospital data surge and information synchronization in the information age, improve the efficiency and accuracy of hospital operation and maintenance management, provide real-time and accurate data support for operation and maintenance teams, and promote the intelligence and efficiency of operation and maintenance work.Methods The system adopted B/S architecture, and the Python 3.11 and Django 4.2 framework were used to realize the development and application of user management, server details, dictionary configuration, data Kanban and other modules. The database used PostgreSQL 15 to implement human-computer interaction in browser manner.Results After the application of the system, the average ledger management time and data entry time of the operation and maintenance personnel were reduced by 46.84% and 55.56%, respectively, and the ledger data error rate was reduced from 5.0% to 0.1%, and the differences were statistically significant (P<0.001). The information difference between the relevant operation and maintenance personnel was eliminated, and the data 0 delay and 100% synchronization were realized.Conclusion The hospital server ledger management system promotes the normalization and standardization of operation and maintenance work, enhances the cooperation ability and response speed of the operation and maintenance team, which lays a solid technical foundation for improving the high-quality development of hospital informatization and high-quality medical services.

Objective To construct and improve the microbiological laboratory information system (MLIS), and achieve the paperless and information management of microbial laboratory.Methods Using C/S three-tier architecture, Oracle database, NET Framework 4.0 development tools and C# programming language, and referring to CLSI M100, ISO 15189 and other standard specifications, combined with the actual work needs of microbial inspectors, the MLIS suitable for the microbial workflow of primary hospitals was developed to realize the recording of the whole process inspection information such as receiving, smearing, inoculation, culture, drug sensitivity test and report of microbial specimens, and grading reporting mechanism.Results After the application of MLIS, the average pretreatment time of specimens was shortened by 81.25%, the smear report time and positive result report time were shortened by 89.46% and 29.54%, respectively (P<0.001), and the classification report rate was increased by 100%.Conclusion The clinical MLIS improves the work efficiency of the microbial laboratory. The electronic records of the whole process management ensure the traceability and reliability of the experimental results. The grading reporting mechanism effectively shortens the reporting time, which helps clinical diagnosis and timely symptomatic treatment, reduces the waste of medical resources, and improves the overall level of medical services.

Deep venous thrombosis (DVT) of the lower extremities serves as the primary thrombotic source for pulmonary embolism, and the two together constitute the pathological progression of venous thromboembolism (VTE). With the incidence of VTE showing a persistent upward trend, it has emerged as a major clinical issue that threatens patient safety. The current standard therapeutic strategies encompass pharmacological anticoagulation, systemic thrombolysis and surgical thrombectomy. However, for patient populations with anticoagulant contraindications, anticoagulant therapy failure or high bleeding risks, inferior vena cava filter (IVCF) implantation shows unique clinical intervention value. This article systematically reviewed the classification characteristics, clinical application features and domestic and international clinical guideline specifications of IVCF. It enumerates the regulatory policies of U.S. FDA on IVCF and uses this as a reference to propose corresponding regulatory measures for IVCF in China, aiming to provide insights for the scientific supervision of such medical devices.

Objective To strengthen the informatization of medical device adverse event monitoring and reporting, to discover the potential risks of medical devices in a timely manner, and improve the efficiency of medical device adverse event risk discovery, reporting and disposal.Methods Taking the data of medical device adverse events from the National Medical Device Adverse Event Monitoring Information System from January 1, 2021 to September 30, 2024 in a city of Shandong as the research object, the RFM model of business intelligence analysis was used to predict and analyze the adverse events of medical devices.Results After applying the RFM intelligent analysis method, 42 typical high-value cases were found, and the active monitoring range could be changed by adjusting the parameter weight. After the implementation of the RFM algorithm model, the risk discovery time of the same registration number decreased from (237.53±38.22) d to (17.13±1.57) d, and the clinical service satisfaction score increased from (85.93±7.27) points to (91.97±4.77) points, and the differences were statistically significant (P<0.05).Conclusion This paper innovatively introduces the RFM model into the field of medical device adverse event monitoring, which can enable analysts to quickly locate high-risk adverse events and further ensure the safe and effective operation of medical devices.

Objective To establish an evaluation system for the centralized management mode of medical equipment, so as to provide reference for the evaluation of management indicators and optimization of management modes.Methods An expert group was established to construct a preliminary draft of the evaluation index system for the centralized management mode of medical equipment through literature review and expert consultation. After two rounds of Delphi expert consultation, the final index system was determined, and the weights of each level of indicators were determined based on the scoring results.Results A total of 12 experts were invited to participate in the evaluation system research. The effective response rates of the two rounds of consultation questionnaires were both 100%, with authoritative coefficients of 0.88054 and 0.84303. The coefficient of variation ranges were 0.0952-0.3934 and 0.0805-0.2513, respectively, and the Kendall’s coordination coefficients were 0.339 and 0.434, respectively, indicating a high degree of coordination. Finally, 3 primary indicators, 7 secondary indicators, and 28 tertiary indicators were determined.Conclusion The evaluation system for the centralized management mode of medical equipment constructed in this study has certain reliability and applicability, and can provide reference value for the evaluation and optimization of management modes.

Objective To explore the effectiveness of supply processing distribution (SPD) projects in the acceptance of medical consumables to verify their important role in the refined management of medical consumables.Methods Based on the refined management of SPD projects in the acceptance of medical consumables, this study summarized the problems in the original acceptance process, such as heavy information input, difficult supervision of licenses and certificates, and unclear warehouse locations. It compares the improvements and optimization results of the acceptance process and information system after implementing the SPD project, including information scanning input, electronic license/certificate supervision, and storage location label management. Statistical methods were used to compare the work effectiveness before and after refined management.Results For non-direct delivery medical consumables, significant differences were found in central warehouse acceptance time, abnormal licenses/certificates management time, acceptance feedback time, storage placement time, secondary warehouse acceptance and inventory time, and acceptance data errors between central and secondary warehouses (P<0.001). For direct delivery medical consumables (cold chain products, orthopedic implant products), significant differences were observed in acceptance time and acceptance errors across different data samples (P<0.001).Conclusion The refined management of medical consumables has achieved remarkable effectiveness in the acceptance process, improving the efficiency of medical consumables acceptance management in medical institutions. This study provides scientific and effective suggestions for other medical institutions to implement refined management of medical consumables.

Objective To conduct a visual analysis of the relevant research in the field of resting-state functional magnetic resonance imaging in the past 10 years, review the research history, and expound the research hotspots and evolution trends.Methods Relevant English literatures published from 2014 to 2023 in the SCI-EXPANDED subdatabase of the Web of Science core collection database were screened, and the knowledge graph was drawn with the help of VOSviewer and CiteSpace software.Results A total of 10581 literatures were ultimately included, and the number of published papers in this field had been increasing year by year. China had the highest number of published articles (4836 papers), and the United States had the highest number of citations (111945 times). Capital Medical University was the institution with the most published papers (420 papers), Gong Qiyong was the author with the most published papers (129 papers), and Frontiers in Neuroscience was the journal with the most published papers (524 papers). The top 5 most frequently used keywords were functional connectivity, default mode network, brain network, connectivity, and cortex. The hot keywords in recent years included support vector machine, degree centrality, machine learning, cognitive function, etc.Conclusion In recent years, the research interest in this field has continued to grow, and the analytical methods have shifted from emerging technologies such as functional connectivity, dimensionality centrality of local consistency, and dynamic functional connectivity. The research content has gradually shifted from exploring the neuroimaging features of brain diseases to the integrated application of imaging and artificial intelligence to achieve precise diagnosis and classification of diseases. Future research is expected to focus on optimizing data analysis methods, deeply exploring the potential of machine learning technology, and expanding its application scope.

Objective By analyzing the previous literature on the imaging diagnosis of atherosclerosis, to reveal the research trends and hotspots in this field in the past 10 years.Methods Relevant literature on the imaging diagnosis of atherosclerosis from 2014 to 2024 was obtained from the PubMed database through thematic search. The R package “bibliometrix” was used for subsequent data mining, and the data visualization processing was completed on the Medical Pulse Bibliometric analysis platform.Results A total of 1177 documents were retrieved in this search, with the number of published papers reaching its peak in 2021. In terms of influence, Zhao Xihai was a highly influential author. The Icahn School of Medicine at Mount Sinai was a high-impact institution; Arherosclerosis was a high-impact journal. In terms of international cooperation, the United States ranked first in both influence and scope in this field. An analysis of the research hotspots reveals that the key words “atherosclerosis” and “magnetic resonance imaging” were respectively the core themes and key technologies, which had extensive influences on the research in the field of imaging diagnosis of atherosclerosis. Recent research hotspots had focused on the integration and innovation of different imaging techniques, while increasing attention to specific diseases. In addition, early diagnosis and targeted therapy had also received attention from researchers.Conclusion This study systematically analyzes the research trends and hot changes in the imaging diagnosis of atherosclerosis in the past 10 years, providing a reference basis for researchers to understand academic dynamics and select research directions.

Objective To investigate the neural mechanisms underlying sustained attention deficits in mild traumatic brain injury (mTBI) patients using 3D-arterial spin labeling (3D-ASL) and the psychomotor vigilance test (PVT).Methods Twenty-nine patients with mTBI (acute and chronic phases) and 25 healthy controls were enrolled. Demographic data, fatigue assessment instrument (FAI), Pittsburgh sleep quality index, and Epworth sleepiness scale scores, as well as PVT-task 3D-ASL data were collected. Scale scores across groups were compared using analysis of variance. Scale scores between the acute and chronic mTBI groups were compared using a paired t-test. PVT reaction times were analyzed using repeated-measures analysis of variance, followed by post hoc testing for further statistical analysis.Results The acute phase group had higher FAI scores than the chronic phase group and the control group, the difference was statistically significant (P<0.05), with no significant differences in other comparisons (P>0.05). PVT behavioral results showed a significant main effect of time on reaction time (P<0.05) and a significant interaction effect between time and group (P<0.05). Reaction times in all stages of the acute phase were longer than those in the control group (P<0.05) and the chronic phase group (P<0.05), while no significant difference was found between the chronic phase group and the control group (P>0.05). Changes in cerebral blood flow (CBF) showed that in the acute phase group, CBF decreased in the parahippocampal gyrus and precuneus, and increased in the frontal and parietal lobes; compared with the control group, CBF increased in the thalamus, frontal lobes, and inferior parietal lobules, and decreased in the parahippocampal gyrus and precuneus, the difference was statistically significant (P<0.05). In the chronic phase group, frontal lobe CBF increased, while CBF decreased in the precuneus and posterior cingulate gyrus; compared with the control group, CBF increased in the anterior cingulate gyrus, middle frontal gyrus, and inferior frontal gyrus, and decreased in the precuneus and inferior parietal lobule, the difference was statistically significant (P<0.05). In the control group, CBF decreased in the posterior cingulate gyrus, middle frontal gyrus, supplementary motor area, and superior temporal gyrus, the difference was statistically significant (P<0.05).Conclusion Sustained attention deficits in mTBI patients resolve partially within one year after injury but persist chronically. Patients show impaired sustained attention in both acute and chronic phases, with partial recovery in the chronic phase that remain below the control group level.

Objective To evaluate the value of combining spectral shaping, automatic tube current modulation (CARE Dose 4D), and the advanced modeled iterative reconstruction algorithm (ADMIRE) for ultra-low-dose chest CT in children.Methods 60 children clinically diagnosed with pneumonia and undergoing chest low-dose CT were enrolled. They were divided into two groups: control group A (conventional low-dose CT, n=30) and experimental Group B (ultra-low-dose CT, n=30). Images of group B were reconstructed using ADMIRE levels 3, 4, and 5, yielding subgroups B₁, B₂, and B₃. Two radiologists independently performed subjective evaluations of images from groups A, B₁, B₂ and B₃. Objective image parameters, radiation dose metrics, and the figure of merit (FOM) were measured, recorded, calculated, and statistically analyzed.Results Subjectively, all groups had subjective scores >1, acceptance rate >90% meeting diagnostic requirements. Inter-group differences were significant (P<0.001), with no significant difference only between group A and B₃, and between group B₁ and B₂ (P>0.05). Objectively, mean CT values of muscle and lung tissue showed no significant differences among groups (P>0.05). Significant overall differences existed among groups for muscle mean SD of muscle, overall mean SD of muscle (SD msub), signal to noise ratio (SNR), contrast to noise ratio (CNR), and FOM (P<0.001). Pairwise comparisons revealed no significant difference only between group A and B₃ for mean SD of muscle, SD msek, SNR, and CNR (P>0.05). FOM values progressively increased across the four groups, with Group B₃ having the highest. Dose in group B was significantly lower, with dose-length product reaching a minimum of 2.2 mGy·cm and effective dose a minimum of 0.04 mSv, representing an 82.4% reduction compared to group A.Conclusion The combined application of spectral shaping, CARE Dose 4D, and ADMIRE significantly reduces radiation dose while optimizing image quality to meet diagnostic requirements for pediatric chest CT, demonstrating substantial clinical value.

Pneumonia is a lung infection caused by microorganisms such as bacteria and viruses. In recent years, applying deep learning techniques to classify pneumonia in chest X-ray images has become one of the important research directions in the field of medical image processing and analysis. Compared to traditional classification methods, deep learning techniques, especially convolutional neural networks (CNN), can better extract useful features from pneumonia images and suppress irrelevant information, detecting lung diseases such as pneumonia earlier and providing patients with earlier treatment, thereby improvingtreatment efficacy. A review and summary of CNN methods for classifying pneumonia in chest X-ray images was conducted. Firstly, two datasets widely used for pneumonia image classification and their evaluation criteria were introduced in detail. Then, the existing problems in manual classification of pneumonia images were pointed out. Subsequently, the research progress of CNN based on these two datasets was highlighted. Finally, the current challenges and future prospects for classifying pneumonia in chest X-ray images were discussed.

As the clinical treatment of chronic pain and spasmodic diseases has gained increasing attention, implantable intrathecal drug delivery systems (IDDS) have become one of the key approaches for managing such conditions. In China, IDDS have been gradually applied in clinical practice for treating various refractory pain and spastic disorders, but the systems remain undomesticated, with imported products carrying high prices. This paper introduced the general structure, performance, and therapeutic scope of IDDS, and summarized the research progress in both software and hardware aspects at home and abroad. By reviewing the current clinical application status of IDDS domestically and internationally, and comparing/analyzing market demands with the monopolistic pricing of imported products, this study clarified the value of further domestication research and discussed the significance of domestic development as well as the clinical application prospects in China.

Pre-operative anxiety is an emotional disorder before an operation, and its occurrence is related to surgical stress and pressure. Pre-operative stress-related anxiety increases anaesthetic doses during surgery and is even associated with a decrease in long-term quality of life and survival after surgery. Traditional preoperative education may suffer from problems such as monotony, formality, and abstract content. The emergence and development of virtual reality (VR) technology offer a new avenue for non-drug intervention in anxiety. Currently, a number of studies have been reported on VR-based intervention for surgical anxiety, particularly in children and for certain surgical procedures. This paper aimed to analyse and evaluate previous clinical studies on VR-based preoperative anxiety intervention, clarify its research direction, and provide references for clinical research in terms of expanding application scenarios, enriching intervention contents, and improving the evaluation system.

As a global public health priority, Parkinson’s disease (PD) patient care has garnered significant public attention. Current clinical management of PD patients faces bottlenecks such as traditional diagnosis relying on subjective experience, lack of personalized home rehabilitation programs, and limited monitoring methods for non-motor symptoms. Although mobile health applications (mHealth APPs) have demonstrated advantages in convenience and cost-effectiveness for chronic disease management, domestic applications are still confined to basic nursing interventions via WeChat, with notable gaps in areas such as auxiliary diagnosis, precise assessment, and integrated traditional Chinese and Western medicine interventions. This paper introduced the application of mHealth APPs in PD patient health management, covering four aspects: assisting disease diagnosis, health assessment, health monitoring, and home rehabilitation training. It proposed that mHealth APPs can facilitate early PD detection, improve patients’ quality of life, and enhance the quality of healthcare services, aiming to provide references for domestic research on mobile health management of PD patients.

Impacted mandibular third molars (IMM3) are common and frequently encountered diseases in oral and maxillofacial surgery, and imaging examinations play a crucial role in their diagnosis and treatment. In recent years, significant breakthroughs have been made in the application of artificial intelligence (AI) in stomatology. Specifically, AI based on deep learning (DL) can accurately identify and segment IMM3 and surrounding anatomical structures. This not only improves the efficiency of correct interpretation of oral images but also provides clinicians with a more intuitive and precise basis for diagnosis and treatment. Currently, DL-based AI technology has become a research hotspot in clinical stomatology. Therefore, this article reviewed the recent application progress, existing challenges, and future development directions of DL-based AI in the diagnosis and treatment of IMM3, aiming to provide intelligent theoretical support and practical guidance for IMM3 management.

Objective To effectively reduce the failure frequency of traditional Chinese medicine fumigators by implementing reliability centered maintenance (RCM) theory.Methods RCM theory was applied to analyze the reliability and operational requirements of the key functional modules of the traditional Chinese medicine fumigator. Failure mode and effects analysis was used to analyze the important functional modules of the device, leading to the development of a preventive maintenance plan for these modules. The maintenance and management system for traditional Chinese medicine fumigator was also improved. A total of 22 traditional Chinese medicine fumigators from the equipment department of Traditional Chinese Medicine Hospital of Huzhou were selected as the study objects. From January to December 2022, a traditional management model was applied for maintenance, and from January to December 2023, an improved management model based on RCM was used. The failure frequencies under both management models were compared.Results After applying the improved management model based on RCM theory, the failure frequency of traditional Chinese medicine fumigator was reduced by 52.2%. Compared with the traditional management model, the failure frequency of the devices significantly decreased, while the operational accuracy rate of users significantly increased (P<0.05). The department’s total satisfaction with the device usage increased by 16% after the adoption of the improved management model.Conclusion The improved maintenance model based on RCM theory effectively reduces the failure frequency of traditional Chinese medicine fumigator, minimizes the risks and safety hazards associated with medical equipment, and provides a reference for the maintenance and management of medical devices.